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Robot Semantic Localization Through CNN Descriptors

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ROBOT 2017: Third Iberian Robotics Conference (ROBOT 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 693))

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Abstract

Semantic localization for mobile robots involves an accurate determination of the kind of place where a robot is located. Therefore, the representation of the knowledge of this place is crucial for the robot. In this paper we present a study for finding a robust model for scene classification procedure for a mobile robot. The proposed system uses CNN descriptors for representing the input perceptions of the robot. First, we develop comparative experiments in order for finding a model. Experiments include the evaluation of several pre-trained CNN models and training a classifier with different classifications algorithms. These experiments were carried out using the ViDRILO dataset and compared with the benchmark provided by their authors. The results demonstrate the goodness of using CNN descriptors for semantic classification.

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Notes

  1. 1.

    The ViDRILO dataset can be freely downloaded from http://www.rovit.ua.es/dataset/vidrilo/.

  2. 2.

    http://www.cs.waikato.ac.nz/ml/weka/index.html.

  3. 3.

    https://cloud.google.com/vision/.

  4. 4.

    Implemented for Keras with TensorFlow.

  5. 5.

    www.ald.softbankrobotics.com/en/cool-robots/pepper/.

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Acknowledgements

This work has been partially supported by the Spanish Government TIN2016-76515-R Grant, supported with Feder funds. José Carlos Rangel is funded by IFARHU grant 8-2014-166 of the Republic of Panamá. Edmanuel Cruz is funded by IFARHU & SENACYT grant 270-2016-207 of the Republic of Panamá.

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Authors and Affiliations

  1. Computer Science Research Institute, University of Alicante, P.O. Box 99, 03080, Alicante, Spain

    Edmanuel Cruz, José Carlos Rangel & Miguel Cazorla

  2. RobotSIS Research Group, Universidad Tecnológica de Panamá, Santiago, Veraguas, Panama

    Edmanuel Cruz & José Carlos Rangel

Authors
  1. Edmanuel Cruz
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  2. José Carlos Rangel
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  3. Miguel Cazorla
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Corresponding author

Correspondence to Edmanuel Cruz .

Editor information

Editors and Affiliations

  1. Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Sevilla, Spain

    Anibal Ollero

  2. Institut de Robòtica I Informàtica Industrial (CSIC-UPC), Universitat Politècnica de Catalunya, Barcelona, Spain

    Alberto Sanfeliu

  3. Departamento de Informática e Ingeniería de Sistemas, Escuela de Ingeniería y Arquitectura, Instituto de Investigación en Ingeniería de Aragón, Zaragoza, Spain

    Luis Montano

  4. Institute of Electronics and Telematics Engineering of Aveiro (IEETA), Universidade de Aveiro, Aveiro, Portugal

    Nuno Lau

  5. IDMEC, Instituto Superior Técnico de Lisboa, Universidade de Lisboa, Lisbon, Portugal

    Carlos Cardeira

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Cruz, E., Rangel, J.C., Cazorla, M. (2018). Robot Semantic Localization Through CNN Descriptors. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-70833-1_46

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  • DOI: https://doi.org/10.1007/978-3-319-70833-1_46

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-70833-1

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